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Now that we have covered the línea, come and fill it up, we'll dive into another example to help highlight

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how to apply the filter to a system with different characteristics.

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We will investigate the pendulum estimation problem in the section.

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The pendulum dynamic system is a great example to show that the linear common filter can be applied

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to a nonlinear problem if the appropriate considerations and approximations are made inside the filter.

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So now let's have a look at the pendulum estimation problem.

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We have a simple pendulum system here that has a mass spin it from a pivot point that allows it to freely

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swing.

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When the mass is released from a non-zero angle, it will swing back and forth.

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Our estimation problem will be to how to estimate the state of the pendulum, which consists of the

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angle of position theta and the angular right theta dot.

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And we're going to do this from a series of noisy measurements of only the angle of the pendulum theta.

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So this section of the course is going to break the pendulum problem down into five different videos.

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The first video is the pendulum estimation problem.

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So that's this video here where be going over what we're actually trying to accomplish in this problem.

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The next is going to be the system and measurement dynamics where we talk about the pendulum motion

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and dynamics directly.

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Next is going to be the common field of model implementation, where we talk about how to model and

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implement the common filter for this particular system.

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Then we're going to have a look at the tuning and performance of the system that we've just implemented.

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And finally, we're going to wrap up with a summary of what we've learned in the section.